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Originating in the Renaissance and burgeoning in the digital era, tablaturesare a commonly used music notation system which provides explicitrepresentations of instrument fingerings rather than pitches. GuitarPro hasestablished itself as a widely used tablature format and software enablingmusicians to edit and share songs for musical practice, learning, andcomposition. In this work, we present DadaGP, a new symbolic music datasetcomprising 26,181 song scores in the GuitarPro format covering 739 musicalgenres, along with an accompanying tokenized format well-suited for generativesequence models such as the Transformer. The tokenized format is inspired byevent-based MIDI encodings, often used in symbolic music generation models. Thedataset is released with an encoder/decoder which converts GuitarPro files totokens and back. We present results of a use case in which DadaGP is used totrain a Transformer-based model to generate new songs in GuitarPro format. Wediscuss other relevant use cases for the dataset (guitar-bass transcription,music style transfer and artist/genre classification) as well as ethicalimplications. DadaGP opens up the possibility to train GuitarPro scoregenerators, fine-tune models on custom data, create new styles of music,AI-powered songwriting apps, and human-AI improvisation.

DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models